Finding scientific topics

@article{Griffiths2004FindingST,
  title={Finding scientific topics},
  author={Thomas L. Griffiths and Mark Steyvers},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  year={2004},
  volume={101},
  pages={5228 - 5235}
}
  • T. Griffiths, M. Steyvers
  • Published 6 April 2004
  • Computer Science
  • Proceedings of the National Academy of Sciences of the United States of America
A first step in identifying the content of a document is determining which topics that document addresses. [] Key Method 3, 993-1022], in which each document is generated by choosing a distribution over topics and then choosing each word in the document from a topic selected according to this distribution. We then present a Markov chain Monte Carlo algorithm for inference in this model. We use this algorithm to analyze abstracts from PNAS by using Bayesian model selection to establish the number of topics…

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